1. TDTS21: Advanced Networking Lecture 8: Online Social Networks Based on slides from P. Gill Revised 2015 by N. Carlsson

2. What are (online) social networks? 2  Social networks are graphs of people  Graph edges connect friends  `Friend’ has different implications  How hard is it to be Facebook `friends’?  Online social networking  Social network hosted by a Web site  Friendship represents shared interest or trust  Online friends may have never met

3. What are online social networks used for? 3  Popular for sharing content  Photos (Flickr), videos (YouTube), blogs (LiveJournal), profiles (Facebook, Orkut)  Fixed broadband (Sandvine Q1 2014) YouTube 5.5% upload, 13.2% down Facebook 2.2% upload, 2.0% down  Popular with users on the go  Mobile (Sandvine Q1 2014) YouTube 3.8% up, 17.6% down Facebook 27.0% up, 14.0% down

4. Why are social networks interesting? 4  Popular way to connect  Estimated 1.32B users online each day  Average American spends 40 minutes/day on the site  Changing the flow of information  Formerly few ``writers’’ many ``readers’’ online  Now anyone can write!  What does this mean for Internet traffic?  Important in regions with strict media controls  E.g., Iran, Egypt using social media platforms to get word out in times of unrest  Useful in times of disaster

5. Notable incidents … 5

6. Not just a social phenomenon… 6 Facebook now contains photo and video  Content delivery challenges! YouTube is a large fraction of Google’s traffic! Understanding properties of these networks is important to understand how we build systems to support them!

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8. A few words about “Rich get richer” and “Preferential attachment” 8

9. A few chirps about Twitter 9  … by Krishnamurthy, Gill, and Arlitt

10. Aside: User relationships on Twitter  Acquaintances  Similar number of followers and following  Along the diagonal  Green portion is top 1- percentile of tweeters 14

11. Aside: User relationships on Twitter  Broadcasters  News outlets, radio stations  No reason to follow anyone  Post playlists, headlines 13

12. Aside: User relationships on Twitter  Miscreants?  Some people follow many users (programmatically)  Hoping some will follow them back  Spam, widgets, celebrities (at top) 15

13. Aside: User relationships on Twitter 13 Twitter noticed the miscreants… … enacted the 10% rule (you can follow 10% more people than follow you)

14. Evolution of an Online Social Aggregation Network: An Empirical Study 14  by Garg et al.

15.  An online social service aggregator  A glimpse into service popularity and usage (although some bias)  Link formation:  Can preferential attachment explain link formations? Any impact of node age?  What influence does factors such as proximity and group affiliation have in link formations? 15 [Garg et al. IMC ‘09]

16. D A C B B follows C B is follower of C C is friend of B 16 [Garg et al. IMC ‘09]

17. Preferential Attachment (PA)  Does PA explain the observed data ?  p i proportional to k i α  For source node selection (Out-degree, α = 0.8)  For destination node selection (In-degree, α = 0.9) C C A A B B 17

18.  We considered subscription to common services as an indicator of common interest. Group Affiliation & Link Formation Source nodes younger than 50 days 18

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20. OSNs: Wrap up 20  Many different types of OSNs  Photos, video, profile-based  Some extremely popular source of much Internet traffic  Facebook, YouTube  New ones emerging  Instagram, snapchat  Old ones fading  MySpace, Friendster  Studying their properties can inform how we build networks and systems to support them!